Advanced Traffic Management System using a Fuzzy Logic Controller to Differentiate Parking Vehicle and Moving Vehicle
Mary N Peter1, Pushpa Rani2

1Mary N Peter*, Ph. D Research Scholar  Mother Theresa Women’s University and Faculty, Department of Computer Science, Kristu Jayanti College, Bangalore.
2Pushpa Rani, Professor and Chairperson, Department of Computer Science of Mother Teresa Women‟s University, India
Manuscript received on February 10, 2020. | Revised Manuscript received on February 19, 2020. | Manuscript published on March 10, 2020. | PP: 488-494 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2213039520/2020©BEIESP | DOI: 10.35940/ijitee.E2213.039520
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Abstract: In smart cities, traffic congestion is one of the significant problems for citizens. Traffic management is an essential one for the quick development of populace and urban movement in metropolitan areas, and traffic blockage is often seeming on streets. To handle different issues for managing traffic on the streets and to help experts in inappropriate arrangement, a smart traffic management system with the IoT (Internet of Things) is proposed in this paper. Mechanisms to utilize IR sensors to distinguish traffic density isn’t easy as smooth a solo vehicle recognized at the last sensor so that it can suggest traffic density in high in any event, even if there is free space before it. A technique to be proposed to solve the previously mentioned issues efficiently is by utilizing the Internet of things for traffic management systems. This paper aims to propose a Fuzzy controller to deal with traffics in smart cities. Fuzzy induction used to compute exact traffic, which separates the parking vehicle and moving vehicle. There is an issue of separating parking and un-parking vehicles in the existing systems. So, we planned to solve this using fuzzy logic. 
Keywords: Smart City, Traffic Control, IoT, Fuzzy Controller, Differentiate Mechanism, and Classification.
Scope of the Article: Network Traffic Characterization and Measurements